Tsallis Entropy for Geometry Simplification
This paper presents a study and a comparison of the use of different information-theoretic measures for polygonal mesh simplification. Generalized measures from Information Theory such as Havrda–Charvát–Tsallis entropy and mutual information have been applied. These measures have been used in the er...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2011-09-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1099-4300/13/10/1805/ |
| _version_ | 1798006508639748096 |
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| author | Miguel Chover Miquel Feixas Mateu Sbert Pascual Castelló Carlos González |
| author_facet | Miguel Chover Miquel Feixas Mateu Sbert Pascual Castelló Carlos González |
| author_sort | Miguel Chover |
| collection | DOAJ |
| description | This paper presents a study and a comparison of the use of different information-theoretic measures for polygonal mesh simplification. Generalized measures from Information Theory such as Havrda–Charvát–Tsallis entropy and mutual information have been applied. These measures have been used in the error metric of a surfaces implification algorithm. We demonstrate that these measures are useful for simplifying three-dimensional polygonal meshes. We have also compared these metrics with the error metrics used in a geometry-based method and in an image-driven method. Quantitative results are presented in the comparison using the root-mean-square error (RMSE). |
| first_indexed | 2024-04-11T12:56:01Z |
| format | Article |
| id | doaj.art-5760f0d24b18465ca2508f2b5cdc02b6 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-11T12:56:01Z |
| publishDate | 2011-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-5760f0d24b18465ca2508f2b5cdc02b62022-12-22T04:23:04ZengMDPI AGEntropy1099-43002011-09-0113101805182810.3390/e13101805Tsallis Entropy for Geometry SimplificationMiguel ChoverMiquel FeixasMateu SbertPascual CastellóCarlos GonzálezThis paper presents a study and a comparison of the use of different information-theoretic measures for polygonal mesh simplification. Generalized measures from Information Theory such as Havrda–Charvát–Tsallis entropy and mutual information have been applied. These measures have been used in the error metric of a surfaces implification algorithm. We demonstrate that these measures are useful for simplifying three-dimensional polygonal meshes. We have also compared these metrics with the error metrics used in a geometry-based method and in an image-driven method. Quantitative results are presented in the comparison using the root-mean-square error (RMSE).http://www.mdpi.com/1099-4300/13/10/1805/information theoryviewpoint information measuresmesh simplification |
| spellingShingle | Miguel Chover Miquel Feixas Mateu Sbert Pascual Castelló Carlos González Tsallis Entropy for Geometry Simplification Entropy information theory viewpoint information measures mesh simplification |
| title | Tsallis Entropy for Geometry Simplification |
| title_full | Tsallis Entropy for Geometry Simplification |
| title_fullStr | Tsallis Entropy for Geometry Simplification |
| title_full_unstemmed | Tsallis Entropy for Geometry Simplification |
| title_short | Tsallis Entropy for Geometry Simplification |
| title_sort | tsallis entropy for geometry simplification |
| topic | information theory viewpoint information measures mesh simplification |
| url | http://www.mdpi.com/1099-4300/13/10/1805/ |
| work_keys_str_mv | AT miguelchover tsallisentropyforgeometrysimplification AT miquelfeixas tsallisentropyforgeometrysimplification AT mateusbert tsallisentropyforgeometrysimplification AT pascualcastello tsallisentropyforgeometrysimplification AT carlosgonzalez tsallisentropyforgeometrysimplification |